In this paper, we provide a detailed study regarding the effect of the AGN on the morphological properties of their host galaxies and the corresponding morphological classification. We studied six parameters commonly used in non-parametric methods, often in combination with machine and deep learning, to classify galaxies in terms of their morphology. These parameters are: Abraham concentration index (CABR), Gini coefficient (GINI), Conselice-Bershady concentration index (CCON), \(M_{20}\)  moment of light (M20), asymmetry index (ASYM), and smoothness (SMOOTH). We used the sample of 8000 local galaxies with visual morphological classification in g-band [1]} to select a sample of 2301 visually classified non-active local galaxies. We simulated their AGN counterparts by adding in their centers an AGN contribution of 5%, 10%, 25%, 50%, and 75% of the total galaxy flux. For the AGN construction for each galaxy we used its corresponding PSF, described by the Moffat function. We then measured in a consistent way the six morphological parameters in both the original images and all simulated images. We finally studied how the presence and relative contribution of the AGN may affect each of the morphological parameters in relation to galaxy morphology, and the final classification of active galaxies. Our main findings are the following:
